Computation Graphs for AAD and Machine Learning: Part III: Application to Derivatives Risk Sensitivities

Antoine Savine

doi:10.1002/wilm.10830

Computation Graphs for AAD and Machine Learning: Part III: Application to Derivatives Risk Sensitivities

Antoine Savine

Institut for Matematiske Fag

Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning

Abstract

Three articles with code, exploring the notion of computation graph, with words, mathematics and code, and application in Machine Learning and finance to compute a vast number of derivative sensitivities with spectacular speed and accuracy.

Originalsprog	Engelsk
Tidsskrift	Wilmott
Udgave nummer	106
Sider (fra-til)	24–39
ISSN	1759-6351
DOI	https://doi.org/10.1002/wilm.10830
Status	Udgivet - 2020

Adgang til dokumentet

10.1002/wilm.10830

Citationsformater

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title = "Computation Graphs for AAD and Machine Learning: Part III: Application to Derivatives Risk Sensitivities",

abstract = "Three articles with code, exploring the notion of computation graph, with words, mathematics and code, and application in Machine Learning and finance to compute a vast number of derivative sensitivities with spectacular speed and accuracy.",

author = "Antoine Savine",

year = "2020",

doi = "10.1002/wilm.10830",

language = "English",

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DO - 10.1002/wilm.10830

M3 - Journal article

SN - 1759-6351

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